Steve Jones

 Can we all agree that "service" accounts suck from a security perspective.  Those are the accounts that you set up so what system/service can talk to another one.  Often this will be a database connection so the application uses one account (and thus one connection pool) to access the database.  These service accounts are sometimes unique to a service or application, but often its a standard

 If you are here its probably because you've tried to get RocksDB working on a Raspberry PI and had the following exception:Exception in thread "main-broker-b066f428-2e48-4d73-91cd-aab782bd9c4c-StreamThread-1" java.lang.UnsatisfiedLinkError: /tmp/librocksdbjni7453541812184957798.so: /tmp/librocksdbjni7453541812184957798.so: cannot open shared object file: No such file or directory (Possible cause

Back when I was a fairly recent graduate I received one of the best pieces of advice I've ever received.  The project was having some delivery pressures and I was seen as crucial to one of the key parts.  As a result my manager was putting pressure on me to cancel my holiday (two weeks of Windsurfing bliss in the Med with friends) with a promise that the company would cover the costs.  I was

And lo a new project did start and there was much wailing and gnashing of teeth, for up on the board had been nailed ten commandments that the project must follow and the developers were sore afraid. Thou shalt put everything in version control, yeah even the meeting minutes, presentations and "requirements documents that aren't even finished yet" for without control everything is chaos Thou

I've been doing a bit recently around DevOps and what I've been seeing is that companies that having been scaling DevOps tend to run into a problem: exactly what is a good boundary for a DevOps team? Now I've talked before about how Microservices are just SOA with a new logo, well there is an interesting piece about DevOps as well, its not actually a brand new thing.  Its an evolution and

Data isn't really respected in businesses, you can see that because unlike other corporate assets there is rarely a decent corporate catalog that shows what exists and who has it.  In the vast majority of companies there is more effort and automation put into tracking laptops than there is into cataloging and curating information. Historically we've sort of been able to get away with this

Over six parts I've gone through a bit of a journey on what Big Data Security is all about. Securing Big Data is about layers Use the power of Big Data to secure Big Data How maths and machine learning helps Why its how you alert that matters Why Information Security is part of Information Governance Classifying Risk and the importance of Meta-Data The fundamental point here is that

So now your Information Governance groups consider Information Security to be important you have to then think about how they should be classifying the risk.  Now there are docs out there on some of these which talk about frameworks.  British Columbia's government has one for instance that talks about High, Medium and Low risk, but for me that really misses the point and over simplifies the

What does your security team look like today? Or the IT equivalent, "the folks that say no".  The point is that in most companies information security isn't actually something that is considered important.  How do I know this?  Well because basically most IT Security teams are the equivalent of the nightclub bouncers, they aren't the people who own the club, they aren't as important as the

In the first three parts of this I talked about how Securing Big Data is about layers, and then about how you need to use the power of Big Data to secure Big Data, then how maths and machine learning helps to identify what is reasonable and was is anomalous. The Target Credit Card hack highlights this problem.  Alerts were made, lights did flash.  The problem was that so many lights flashed and

In the first two parts of this I talked about how Securing Big Data is about layers, and then about how you need to use the power of Big Data to secure Big Data.  The next part is "what do you do with all that data?".   This is where Machine Learning and Mathematics comes in, in other words its about how you use Big Data analytics to secure Big Data. What you want to do is build up a picture of

In the first part of Securing Big Data I talked about the two different types of security.  The traditional IT and ACL security that needs to be done to match traditional solutions with an RDBMS but that is pretty much where those systems stop in terms of security which means they don't address the real threats out there, which are to do with cyber attacks and social engineering.  An ACL is only

As Big Data and its technologies such as Hadoop head deeper into the enterprise so questions around compliance and security rear their heads. The first interesting point in this is that it shows the approach to security that many of the Silicon Valley companies that use Hadoop at scale have taken, namely pretty little really.  It isn't that protecting information has been seen as a massively

I'm an Uber user, its a great service outside of cities with decent public transport.  But I have been thinking about where they will justify the $17bn valuation and give people a return on that $1.2bn investment.  At the same time I've been following the autonomous car pieces with interest and I think there is a pretty clear way this can end, especially as Uber have already said they are going

In six years Microsoft has come from almost zero corporate knowledge about how cloud computing works to it being an integral part of their strategy.  Sure back in early 2008 there were some pieces of Microsoft that knew about cloud but that really wasn't a corporate view it was what a very few people inside the company knew. How do I know this? Well back in 2008 I was sitting on the top of a

In every change there are hype machines that over play and sages who call doom.  Into the Big Data arena steps David Searls to proclaim that Big Data is a myth and simply hype which is set to burst in an article over at ZDNet. But big data, he said, is nothing more than the myth that collecting vast amounts of data can help companies know customers better than those customers even know

The seminal book on Open Source development "Cathedral and the Bazaar" talks eloquently about the difference between commercial software development and open source development.  In the past few years however there has been another shift, a shift where companies are actively releasing their technology into Open Source as a competitive differentiation.  A claim of 'we are open' because the source

I'm going to state a sacrilegious position for a moment: the quality of data isn't a primary goal in Master Data Management Now before the perfectly correct 'Garbage In, Garbage Out' statement let me explain.  Data Quality is certainly something that MDM can help with but its not actually the primary aim of MDM. MDM is about enabling collaboration, collaboration is about the cross-reference

Over the last few years there has been a trend of increased spending on BI, and that trend isn't going away.  The analyst predictions however have, understandably, been based on the mentality that the choice was between a traditional EDW/DW model or Hadoop.  With the new 'Business Data Lake' type of hybrid approach its pretty clear that the shift is underway for all vendors to have a hybrid

There is a massive amount of IT hype that is focused on what people see, its about the agile delivery of interfaces, about reporting, visualisation and interactional models.  If you could weight hype then it is quite clear that 95% of all IT is about this area.  Its why we need development teams working hand-in-hand with the business, its why animations and visualisation are massively important.